class_docstr: compute planarity and return false if the planarity of a pointcloud is above or below a threshold
  
  Parameters
  ----------
  thresh: float, optional
      threshold to filter low planar pointcloud
  is_leq: bool, optional
      choose whether planarity should be lesser or equal than the threshold or greater than the threshold.
class_docstr_tok: ["compute","planarity","and","return","false","if","the","planarity","of","a","pointcloud","is","above","or","below","a","threshold","Parameters","--","--","--","--","--","thresh",":","float",",","optional","threshold","to","filter","low","planar","pointcloud","is_leq",":","bool",",","optional","choose","whether","planarity","should","be","lesser","or","equal","than","the","threshold","or","greater","than","the","threshold","."]
code: def __call__(self, data):
      if getattr(data, "eigenvalues", None) is None:
          data = PCACompute()(data)
      planarity = compute_planarity(data.eigenvalues)
      if self.is_leq:
          return planarity <= self.thresh
      else:
          return planarity > self.thresh
  
file_path: torch-points3d/torch_points3d/core/data_transform/filters.py
imports: import numpy
  import torch
  import random
  from torch_points3d.core.data_transform.features import PCACompute, compute_planarity
label_desc: Use image node_id 2 for calling the PlanarityFilter obj's underlying member method code with example usage: obj.__call__(data) and returns: unknown, unknown